Methods and apparatus to process measurements associated with drilling operations

ABSTRACT

Methods and apparatus to process measurements associated with drilling operations are described. An example method of modifying processing results during a subterranean formation drilling operation includes identifying a plurality of parameters and processing measurements associated with the subterranean formation obtained while drilling and the plurality of parameters to generate first results. Additionally, the example method includes processing measurements associated with the subterranean formation obtained while drilling is temporarily suspended and the plurality of parameters to generate second results and comparing the first and second results. Further, the example method includes, in response to the comparison of the first and second results, modifying the first results based on the second results to improve a quality of the first results.

FIELD OF THE DISCLOSURE

This patent relates generally to drilling operations and, moreparticularly, to methods and apparatus to process measurementsassociated with drilling operations.

BACKGROUND

During drilling operations, measurements may be obtained and processedwhile drilling or while drilling is temporarily suspended. The processedmeasurements or processing results may be used to obtain a betterunderstanding of the formation being drilled. However, becausemeasurements obtained while drilling may have relatively large amountsof noise, portions of the formation may be inaccurately or inadequatelyunderstood.

SUMMARY

An example method of modifying processing results during a subterraneanformation drilling operation includes identifying a plurality ofparameters and processing measurements associated with the subterraneanformation obtained while drilling and the plurality of parameters togenerate first results. Additionally, the example method includesprocessing measurements associated with the subterranean formationobtained while drilling is temporarily suspended and the plurality ofparameters to generate second results and comparing the first and secondresults. Further, the example method includes, in response to thecomparison of the first and second results, modifying the first resultsbased on the second results to improve a quality of the first results.

An example drillstring includes a measurement device to measure one ormore parameters and a processor to process the one or more measuredparameters and one or more processing parameters to generate results.Additionally, the example drillstring includes an apparatus to linkresults generated during a first time interval and results generatedduring a second time interval.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an example wellsite drilling system.

FIG. 2 depicts an example sonic logging-while-drilling tool.

FIGS. 3-6 depict sonic while drilling tools having one or more seismicsources and one or more receivers.

FIG. 7 depicts an example apparatus that may be used to implement theexamples described herein.

FIG. 8 depicts an example graph of processing results obtained using theexamples described herein.

FIG. 9 depicts a plot of processing results obtained using the examplesdescribed herein.

FIG. 10 is a flowchart of an example method that may be used toimplement the examples described herein.

FIG. 11 is a schematic illustration of an example processor platformthat may be used and/or programmed to implement any or all of theexample methods and apparatus described herein.

DETAILED DESCRIPTION

In the following detailed description of the preferred embodiments,reference is made to the accompanying drawings, which form a parthereof, and within which are shown by way of illustration specificembodiments by which the invention may be practiced. It is to beunderstood that other embodiments may be utilized and structural changesmay be made without departing from the scope of the invention.

The example methods and apparatus described herein can be used toprocess measurements associated with a drilling operation by utilizing aprediction operation or apparatus to perform quality control on resultsobtained while drilling, to set or determine processing parametersand/or to constrain logs forwards and/or to refine logs backwards. Thus,the example methods and apparatus described herein may be used toimprove or optimize the use of measurements and/or the processing ofsuch measurements associated with a drilling operation.

To perform quality control on the results obtained while drilling, theprediction operation or apparatus may utilize measurements or results ofprocessing such measurements obtained while drilling is temporarilysuspended to identify measurements or results obtained while drillingthat are not substantially associated with noise. For example, if themeasurements or processing results are associated with peaks withrespect to slowness in a slowness time coherence map (e.g., slownesspeaks), the prediction operation or apparatus may link slowness peakshaving a relatively high coherence and obtained while drilling and whiledrilling is temporarily suspended. Slowness peaks having a relativelyhigh coherence are not substantially associated with noise. Thereafter,the linked slowness peaks may be advantageously utilized to produce logsthat more accurately represent the formation.

FIG. 1 illustrates a wellsite system 100 in which the examples describedherein can be employed. The wellsite system 100 can be onshore oroffshore. In this example, a borehole 102 is formed in a subsurfaceformation F by rotary drilling. However, directional drilling may alsobe used.

A drillstring 104 is suspended within the borehole 102 and has abottomhole assembly 106 that includes a drill bit 108 at its lower end.At the surface, the wellsite system 100 includes a platform and derrickassembly 110 positioned over the borehole 102. The platform and derrickassembly 110 includes a rotary table 112, a kelly 114, a hook 116 and arotary swivel 118. The rotary table 112 may engage the kelly 114 at anupper end of the drillstring 104 to impart rotation to the drillstring104. The rotary table 112 may be energized by a device or system notshown. The drillstring 104 is suspended from the hook 116 that isattached to a traveling block (also not shown). Additionally, thedrillstring 104 is positioned through the kelly 114 and the rotaryswivel 118, which permits rotation of the drillstring 104 relative tothe hook 116. Additionally or alternatively, a top drive system may beused to impart rotation to the drillstring 104.

In the example depicted in FIG. 1, at the surface, the wellsite system100 includes drilling fluid or mud 120 that may be stored in a pit 122formed at the wellsite. A pump 124 delivers the drilling fluid 120 tothe interior of the drillstring 104 via a port in the rotary swivel 118,causing the drilling fluid 120 to flow downwardly through thedrillstring 104 as indicated by the directional arrow 126. The drillingfluid 120 exits the drillstring 104 via ports in the drill bit 108, andthen circulates upwardly through the annulus region between the outsideof the drillstring 104 and a wall 128 of the borehole 102 as indicatedby the directional arrows 130. The drilling fluid 120 lubricates thedrill bit 108 and carries formation cuttings up to the surface as thedrilling fluid 120 is returned to the pit 122 for recirculation.

The bottomhole assembly 106 of the example illustrated in FIG. 1includes a logging-while-drilling (LWD) module 132, ameasuring-while-drilling (MWD) module 134, another drillstring component136 such as, a roto-steerable system or mud motor, and the drill bit108.

The LWD module 132 may be housed in a drill collar 138 and may includeone or more logging tools. In some examples, the bottomhole assembly 106may include an additional LWD module and/or a MWD module as representedby reference numeral 140. As such, references throughout thisdescription to reference numeral 132 may additionally or alternativelyinclude reference numeral 140. The LWD module 132 may includecapabilities for measuring, processing, and storing information, as wellas for communicating with the surface equipment. Additionally oralternatively, the LWD module 132 may include a seismic measuring device142.

The MWD module 134 may be also housed in a drill collar 143 and caninclude one or more devices for measuring characteristics of thedrillstring 104 and/or the drill bit 108. Additionally or alternatively,the MWD module 134 may include an apparatus (not shown) for generatingelectrical power for at least portions of the bottomhole assembly 106,for example. The apparatus for generating electrical power may include amud turbine generator powered by the flow of drilling fluid. However,other power and/or battery systems may additionally or alternatively beemployed. The MWD module 134 may include one or more tools or measuringdevices such as, for example, a weight-on-bit measuring device, a torquemeasuring device, a vibration measuring device, a shock measuringdevice, a stick slip measuring device, a direction measuring deviceand/or an inclination measuring device.

A logging and control computer 144 and/or a controller 146 may processmeasurement data, parameters and/or information obtained during adrilling operation (e.g., while drilling and/or while drilling istemporarily suspended) using one or more processing parameters to obtainresults (e.g., a log of slowness peaks versus depth). The processing mayinvolve semblance processing, dispersion analysis, wave separationand/or automatic filtering among other processing techniques and theresults of this processing may be associated with or be used to produceslowness logs or dispersion curves, for example. The processingparameters may be associated with formation slowness for P and S waves,formation density, drilling fluid slowness, drilling fluid density,borehole diameter, estimated arrival times of different waves and/orlocal knowledge of the formation, for example. Some of the measurementdata may include formation compressional slowness, formation shearslowness, resistivity measurements, nuclear magnetic resonance (NMR)measurements, a slowness time coherence map, velocity versus frequencyamong other types of measurement data and/or measurements associatedwith formation evaluation.

During drilling operations, processing conducted while drilling (e.g.,during a first time interval) may produce results having relativelylarge amounts of noise and processing conducted while drilling istemporarily suspended (e.g., during a second time interval) such as,when additional drillpipe is added to the drillstring, may produceresults having relatively small amounts of noise. To enable the examplesdescribed herein to identify useful (e.g., relatively accurate)information from the processing results obtained while drilling, topredict processing results while drilling and/or to optimize theprocessing results, the logging and control computer 144 and/or thecontroller 146 may be provided with a Kalman filter, a recursive filter,a particle filter or any other suitable device (e.g., an apparatus toimplement a prediction operation) 148 or 150. The Kalman filter 148and/or 150 may utilize the processing results obtained while drilling istemporarily suspended to identify results within the processing resultsobtained while drilling that are not substantially associated withnoise, thereby effectively constraining the processing results obtainedwhile drilling. If any of the processing results (e.g., the processingresults obtained while drilling) are identified as being inaccurate,such processing results may be corrected (e.g., modified, refined) bythe amount of error identified (e.g., smoothed back) or such results maybe flagged for later analysis.

Identifying the processing results obtained while drilling that are notsubstantially associated with noise may be accomplished by selectivelyassociating and/or linking the processing results obtained whiledrilling is temporarily suspended and the processing results obtainedwhile drilling, for example. The processing results may be associatedwith slowness peaks. In such examples, by linking slowness peaks havingrelatively high coherence, slowness peaks obtained while drilling thatare not substantially associated with noise may be identified.Thereafter, the linked slowness peaks may be advantageously utilized toproduce logs that more accurately represent the formation. The resultsmay be presented versus depth in a slowness time (ST) projection. Inother examples, the processing results may be associated with slownessat different frequencies. In such examples, by identifying resultshaving relatively high coherence at a particular frequency, resultsobtained while drilling that are not substantially associated with noisemay be identified. Using such an approach, slowness may be determinedand plotted for different frequencies to produce dispersion curves.

The Kalman filter 148 and/or 150 may utilize the processing resultsobtained while drilling is temporarily suspended to estimate or predictprocessing results (e.g., future processing results, past processingresults) obtained while drilling, for example. Such an approach, may beadvantageously utilized to constrain, modify and/or refine processingresults or logs generated using the examples described herein backwards(e.g., previous or past results) and forward (e.g., future results) toimprove a quality and/or characteristic of the processing resultsobtained while drilling, for example. Additionally or alternatively, theprocessing results obtained while drilling is temporarily suspended maybe utilized to update or modify the processing parameters (e.g., theborehole diameter, the drilling fluid density, etc.) if the previousparameters are no longer applicable and/or the processing resultsobtained while drilling is temporarily suspended are different than theprocessing results obtained while drilling or are different thanprevious processing results obtained while drilling was temporarilysuspended. In some examples, if the processing results obtained whiledrilling is temporarily suspended in a second silent zone are differentfrom previous processing results obtained while drilling is temporarilysuspended in a first silent zone, the processing results obtained in thesecond silent zone may be utilized to predict previous processingresults and/or to correct for errors in (e.g., smooth back) processingresults between the first and second silent zones.

The processing results obtained while drilling, while drilling istemporarily suspended and/or predicted by the Kalman filter 148 and/or150 may be utilized by the logging and control computer 144 and/or thecontroller 146 to generate log(s). The log(s) may be a slowness logversus depth, cross-logs and/or real-time logs, for example. In someexamples, one of the logs may be a silent log generated using theprocessing results obtained while drilling is temporarily suspended. Thesilent log may have relatively high quality and a vertical resolutionassociated with an interval (e.g., 60 feet, 90 feet) drilled beforeadditional drillpipe is added to the drillstring. Additionally oralternatively, one of the logs may be a noisy log generated using theprocessing results obtained while drilling. The noisy log may have arelatively fine vertical resolution and have questionable or challengingquality at times. Additionally or alternatively, one of the logs may bea predicted log generated using the processing results obtained whiledrilling is temporarily suspended in conjunction with the Kalman filter148 and/or 150. Any or all of these logs may be compared by, forexample, overlaying the logs to identify similarities and/or differencesand/or to identify portions of the noisy log associated with noiseand/or that dramatically depart from the silent log and/or the predictedlog.

The logging and control computer 144 may receive information and/or datatransmitted from the LWD module 132, the seismic measuring device 142and/or the MWD module 134. The logging and control computer 144 mayanalyze results obtained while drilling and while drilling istemporarily suspended. The logging and control computer 144 may includea user interface that enables parameters (e.g., processing parameters)to be input and/or outputs to be displayed. While the logging andcontrol computer 144 is depicted uphole and adjacent the wellsitesystem, a portion or the entire logging and control computer 144 may bepositioned in the drillstring 104, the bottomhole assembly 106 and/or ina remote location.

Although the components of FIG. 1 are shown and described as beingimplemented in a particular conveyance type, the example methods andapparatus described herein are not limited to a particular conveyancetype but, instead, may be implemented in connection with differentconveyance types including, for example, coiled tubing, wireline, wireddrillpipe, and/or any other conveyance types known in the industry.

FIG. 2 depicts a sonic logging-while-drilling tool 200 that may be usedto implement at least a part of the LWD module 132 of FIG. 1 or may bepart of the LWD module 140 as described in U.S. Pat. No. 6,308,137,which is hereby incorporated herein by reference in its entirety. Anoffshore rig 202 having a sonic transmitting source or array ortransmitter 204 may be deployed near a surface 206 of water 208.Additionally or alternatively, any other type of uphole or downholesource or transmitter may be provided to transmit sonic signals. In someexamples, an uphole processor (not shown) may control the firing of thetransmitter 204.

Uphole equipment 210 may also include acoustic receivers (not shown) anda recorder (not shown) for capturing reference signals near the sourceof the signals (e.g., the transmitter 204). The uphole equipment 210 mayalso include telemetry equipment (not shown) for receiving MWD signalsfrom downhole equipment 212. The telemetry equipment and the recorderare typically coupled to a processor (not shown) so that recordings maybe synchronized using uphole and downhole clocks (not shown). In thisexample, a downhole LWD module 214 includes one or more acousticreceivers 216 and 218. The acoustic receivers 216 and 218 are typicallycoupled to a signal processor 220 so that recordings may be made ofsignals detected by the receiver(s) 216 and/or 218 in synchronizationwith the firing of the signal source (e.g., the transmitter 204).

FIGS. 3-6 illustrate seismic-while-drilling tools 300, 400, 500 and/or600 that may be used to implement at least a part of the LWD module 132of FIG. 1 or may be part of the LWD module 140 as described in P. Bretonet al., “Well Positioned Seismic Measurements,” Oilfield Review, pp.32-45, Spring, 2002, which is hereby incorporated herein by reference inits entirety. The seismic-while-drilling tools 300, 400, 500 and 600 mayinclude a single receiver 302 (FIG. 3) and 402 (FIG. 4) or a pluralityof receivers 502-506 (FIG. 5), 602-616 (FIG. 6) that may be employed inconjunction with a single seismic source or transmitter 304 (FIG. 3),508 (FIG. 5) or a plurality of seismic sources or transmitters 404-414(FIG. 4) or 618-632 (FIG. 6).

FIG. 3 depicts a signal 306 reflecting off of a bed boundary 308 and maybe referred to as a “zero-offset” vertical seismic profile arrangement.FIG. 4 depicts signals 416-426 reflecting off of a bed boundary 430 andmay be referred to as a “walkaway” vertical seismic profile arrangement.FIG. 5 depicts signals 510-514 refracting through salt dome boundaries516 and may be referred to as “salt proximity” vertical seismic profile.FIG. 6 depicts signals 634-648 some of which are reflecting off of a bedboundary 650 and may be referred to as “walk above” vertical seismicprofile.

FIG. 7 depicts an example apparatus 700 that may be used to implement aportion of the seismic measuring device 142 (FIG. 1), the LWD module 132(FIG. 1), the logging and control computer 144 (FIG. 1), the controller146 (FIG. 1), the Kalman filter 148 and/or 150 (FIG. 1), the soniclogging-while-drilling tool 200 (FIG. 2) and/or any of theseismic-while-drilling tools 300 (FIG. 3), 400 (FIG. 4), 500 (FIG. 5)and/or 600 (FIG. 6). The apparatus 700 may include a measurement device702, a processor 704, a Kalman filter, a recursive filter, a particlefilter or any other suitable device (e.g., an apparatus to implement aprediction operation) 706 and a data store 708, all or some of which maybe communicatively coupled together. The apparatus 700 may be positionedentirely downhole or partially downhole and partially uphole, forexample.

To measure parameters and/or quantities related to formation properties,the apparatus 700 is provided with the measurement device 702. Themeasurement device 702 may measure formation compressional slowness,formation shear slowness, resistivity measurements, nuclear magneticresonance (NMR) measurements, a slowness time coherence map, velocityversus frequency among other measurements associated with formationevaluation.

To process the measurement data, parameters and/or information obtainedduring a drilling operation along with one or more processingparameters, the apparatus 700 includes the processor 704. The processor704 may process measurements while drilling or while drilling istemporarily suspended. However, processing conducted while drilling(e.g., during a first time interval) may produce results having a firstamount of noise (e.g., a relatively large amount of noise) andprocessing conducted while drilling is temporarily suspended (e.g.,during a second time interval) such as, when additional drillpipe isadded to the drillstring, may produce results having a second amount ofnoise (e.g., a relatively small amount of noise).

Prior to initiating a drilling operation and/or when more up-to-dateinformation becomes available, processing parameters may be input intothe logging and control computer 144, stored in the data store 708and/or updated or changed based on processing results, for example. Theprocessing parameters may be associated with formation slowness for Pand S waves, formation density, drilling fluid slowness, drilling fluiddensity, borehole diameter, estimate time arrival of different wavesand/or local knowledge of the formation. As described above, processingmay include semblance processing, dispersion analysis, wave separationand/or automatic filtering among other types of processing.

To identify useful (e.g., relatively accurate) information from theprocessing results obtained while drilling and/or to predict processingresults while drilling, the apparatus 700 may be provided with theKalman filter 706. The Kalman filter 706 may utilize the processingresults obtained while drilling is temporarily suspended to identifyresults within the processing results obtained while drilling that arenot substantially associated with noise. Identifying results within theprocessing results obtained while drilling that are not substantiallyassociated with noise may be accomplished by comparing (e.g.,similarities and differences) between the processing results obtainedwhile drilling is temporarily suspended and the processing resultsobtained while drilling, for example. If portions of the processingresults obtained while drilling are relatively similar to the processingresults obtained while drilling is temporarily suspended, then theseportions of the processing results obtained while drilling may not besubstantially associated with noise.

The Kalman filter 706 may utilize the processing results obtained whiledrilling is temporarily suspended to predict processing results (e.g.,future processing results, previous or past processing results) obtainedwhile drilling. Additionally or alternatively, the processing resultsobtained while drilling is temporarily suspended may be utilized toupdate or modify the processing parameters (e.g., the borehole diameter,the drilling fluid density, etc.) if the processing results obtainedwhile drilling are different from the processing results obtained whiledrilling is temporarily suspended, for example.

Turning to FIG. 8, the processing results obtained while drilling, whiledrilling is temporarily suspended and/or predicted by the Kalman filter706 may be utilized by the processor 704 (FIG. 7) to generate log(s)represented by graph 800. The y-axis 802 of the graph 800 may beassociated with slowness and the x-axis 804 of the graph 800 may beassociated with depth. In this example, the graph includes a first log806, a second log 808 and a third log 810. The first log 806 may be asilent log generated using the processing results obtained whiledrilling is temporarily suspended. The second log 808 may be a noisy loggenerated using the processing results obtained while drilling. Thethird log 810 may be a predicted log generated using the processingresults obtained while drilling is temporarily suspended in conjunctionwith the Kalman filter 706.

FIG. 9 depicts a plot 900 of slowness peaks 902-932 obtained in drillingzones (i.e., while drilling) 934 and 936 and silent zones (i.e., whiledrilling is temporarily suspended) 938 and 940. Some of the peaks in thedrilling zone 934 and/or 936 are due to noise. Therefore, to select theslowness peak(s) in the drilling zone 934 and/or 936 that is notsubstantially associated with noise, the Kalman filter 148, 150 and/or706 may selectively associate and/or link the slowness peak 916 in thesilent zone 938 with one of the slowness peaks 920-926 in the drillingzone 936 that is substantially coherent, for example. By comparing theslowness peaks 916 and 920-926, the Kalman filter 148, 150 and/or 706may identify high coherence between the slowness peaks 916 and 924 andthat the slowness peaks 920, 922 and 926 are due to noise. Additionally,the Kalman filter 148, 150 and/or 706 may link the slowness peak 932 inthe silent zone 940 with one of the slowness peaks 920-926 in thedrilling zone 936 that is substantially coherent, for example. Bycomparing the slowness peaks 932 and 920-926, the Kalman filter 148, 150and/or 706 may identify high coherence between the slowness peaks 924and 932 and that the slowness peaks 920, 922 and 926 are due to noise.By linking the processing results not substantially associated withnoise, more accurate representations of the formation may be obtainedand/or generated.

FIG. 10 is a flowchart of an example method 1000 that can be used inconjunction with the example apparatus described herein to identifyuseful (e.g., relatively accurate) information from the processingresults obtained while drilling and/or to predict processing resultswhile drilling, for example. The example method 1000 of FIG. 10 may beused to implement the seismic measuring device 142 (FIG. 1), the LWDmodule 132 (FIG. 1), the logging and control computer 144 (FIG. 1), thecontroller 146 (FIG. 1), the Kalman filter 148 and/or 150 (FIG. 1), thesonic logging-while-drilling tool 200 (FIG. 2), any of theseismic-while-drilling tools 300 (FIG. 3), 400 (FIG. 4), 500 (FIG. 5),600 (FIG. 6) and/or the apparatus 700 (FIG. 7). The example method 1000of FIG. 10 may be implemented using software and/or hardware. In someexample implementations, the flowchart can be representative of examplemachine readable instructions, and the example method 1000 of theflowchart may be implemented entirely or in part by executing themachine readable instructions. Such machine readable instructions may beexecuted by the logging and control computer 144 (FIG. 1), thecontroller 146 (FIG. 1) and/or the processor 704 (FIG. 7), for example.

In particular, a processor or any other suitable device to executemachine readable instructions may retrieve such instructions from amemory device (e.g., a random access memory (RAM), a read only memory(ROM), etc.) and execute those instructions. In some exampleimplementations, one or more of the operations depicted in the flowchartof FIG. 10 may be implemented manually. Although the example method 1000is described with reference to the flowchart of FIG. 10, persons ofordinary skill in the art will readily appreciate that other methods toimplement the seismic measuring device 142 (FIG. 1), the LWD module 132(FIG. 1), the logging and control computer 144 (FIG. 1), the controller146 (FIG. 1), the Kalman filter 148 and/or 150 (FIG. 1), the soniclogging-while-drilling tool 200 (FIG. 2), any of theseismic-while-drilling tools 300 (FIG. 3), 400 (FIG. 4), 500 (FIG. 5),600 (FIG. 6) and/or the apparatus 700 (FIG. 7) may additionally oralternatively be used. For example, the order of execution of the blocksdepicted in the flowchart of FIG. 10 may be changed and/or some of theblocks described may be rearranged, eliminated, or combined.

The method 1000 may begin by identifying one or more processingparameters prior to drilling (block 1002). Some of the processingparameters may include or be associated with formation slowness for Pand S waves, formation density, drilling fluid slowness, drilling fluiddensity, borehole diameter, estimated arrival times of different wavesand/or local knowledge of the formation, for example. The processingparameters may be input or set using the logging and control computer144.

The method 1000 may then begin drilling (block 1004) through theformation. As the drilling operation takes place, measurements may beobtained (block 1006) relating to formation parameters and/or quantitiesrelated to formation properties. In some examples, the seismic measuringdevice 142 may be utilized to obtain at least some of the measurements.Some of the measurements and/or formation parameters may be associatedwith formation compressional slowness, formation shear slowness,resistivity measurements, nuclear magnetic resonance (NMR) measurements,a slowness time coherence map, velocity versus frequency and/ormeasurements associated with formation evaluation.

The method 1000 may then perform processing while drilling (block 1008).Specifically, measurements along with the processing parameters may beprocessed to obtain first results. The processing may include semblanceprocessing, dispersion analysis, wave separation and/or automaticfiltering and may be conducted using the logging and control computer144 (FIG. 1), the controller 146 (FIG. 1) and/or the processor 704 (FIG.7), for example. Processing that takes place while drilling may includerelatively large amounts of noise. The method 1000 may then temporarilysuspend drilling (block 1010) to add additional drillpipe to thedrillstring, for example. While drilling is temporarily suspended,measurements may be obtained (block 1012) that may be similar to themeasurements obtained while drilling. The measurements may then beprocessed (block 1014) along with the processing parameters to obtainsecond results. Processing results obtained while drilling istemporarily suspended may include relatively small amounts of noise.

The method 1000 may then compare the results of processing whiledrilling (e.g., the first results) to the results of processing whiledrilling is temporarily suspended (e.g., the second results) (block1016) using the logging and control computer 144 (FIG. 1), thecontroller 146 (FIG. 1) and/or the processor 704 (FIG. 7). The method1000 then determines if there is a difference between the processingresults obtained while drilling and the processing results obtainedwhile drilling is temporarily suspended (block 1018). If there is nodifference between the processing results, control advances to block1024. However, if there is a difference between the processing results,control advances to block 1020.

If there is a difference between the processing results, the method 1000may predict, modify and/or refine the results obtained while drillingusing the Kalman filter 148 and/or 150 (FIG. 1) and/or 706 (FIG. 7)(block 1020). For example, the method 1000 may utilize the processingresults obtained while drilling is temporarily suspended to identifyresults within the processing results obtained while drilling that arenot substantially associated with noise by comparing the processingresults obtained while drilling is temporarily suspended and theprocessing results obtained while drilling. Additionally oralternatively the method 1000 may utilize the processing resultsobtained while drilling is temporarily suspended to predict processingresults (e.g., future processing results, previous processing results)obtained while drilling.

The method 1000 may then predict new or update the processing parametersbased, at least in part, on the processing results obtained whiledrilling is temporarily suspended (block 1022). The method 1000 thendetermines whether it should resume drilling (block 1024). If the method1000 determines that it should resume drilling, control advances toblock 1026 and thereafter to block 1006, otherwise the example method1000 is ended.

FIG. 11 is a schematic diagram of an example processor platform P100that may be used and/or programmed to implement to implement the loggingand control computer 144 (FIG. 1), the controller 146 (FIG. 1) and/orthe processor 704 (FIG. 7). For example, the processor platform P100 canbe implemented by one or more general purpose processors, processorcores, microcontrollers, etc.

The processor platform P100 of the example of FIG. 11 includes at leastone general purpose programmable processor P105. The processor P105executes coded instructions P110 and/or P112 present in main memory ofthe processor P105 (e.g., within a RAM P115 and/or a ROM P120). Theprocessor P105 may be any type of processing unit, such as a processorcore, a processor and/or a microcontroller. The processor P105 mayexecute, among other things, the example methods and apparatus describedherein.

The processor P105 is in communication with the main memory (including aROM P120 and/or the RAM P115) via a bus P125. The RAM P115 may beimplemented by dynamic random-access memory (DRAM), synchronous dynamicrandom-access memory (SDRAM), and/or any other type of RAM device, andROM may be implemented by flash memory and/or any other desired type ofmemory device. Access to the memory P115 and the memory P120 may becontrolled by a memory controller (not shown).

The processor platform P100 also includes an interface circuit P130. Theinterface circuit P130 may be implemented by any type of interfacestandard, such as an external memory interface, serial port, generalpurpose input/output, etc. One or more input devices P135 and one ormore output devices P140 are connected to the interface circuit P130.

The examples described herein can be used to identify accurateprocessing results generated during a drilling operation by utilizing aprediction operation or apparatus. Specifically, by utilizing aprediction operation or apparatus in conjunction with processing resultsgenerated while drilling is temporarily suspended, non-noisy processingresults generated while drilling may be identified. By identifyingnon-noisy processing results and utilizing these processing results whengenerating formation representative logs, the examples described hereinsubstantially avoid the inclusion of processing results that arenon-representative of the formation due to noise when generating suchlogs, for example.

Although certain example methods, apparatus and articles of manufacturehave been described herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe appended claims either literally or under the doctrine ofequivalents.

1. A method of modifying processing results during a subterraneanformation drilling operation, comprising: identifying a plurality ofparameters; processing measurements associated with the subterraneanformation obtained while drilling and the plurality of parameters togenerate first results; processing measurements associated with thesubterranean formation obtained while drilling is temporarily suspendedand the plurality of parameters to generate second results; comparingthe first and second results; and in response to the comparison of thefirst and second results, modifying the first results based on thesecond results to improve a quality of the first results.
 2. The methodas defined in claim 1, wherein the measurements obtained while drillingcomprise measurements having a first amount of noise and themeasurements obtained while drilling is temporarily suspended comprisemeasurements having a second amount of noise that is less than the firstamount of noise.
 3. The method as defined in claim 1, wherein modifyingthe first results based on the second results comprises constraining thefirst results.
 4. The method as defined in claim 1, wherein modifyingthe first results based on the second results comprises identifying oneor more peaks within the first results that are not substantiallyassociated with noise.
 5. The method as defined in claim 4, wherein theone or more peaks comprise one or more peaks with respect to slowness ina slowness time coherence map.
 6. The method as defined in claim 1,wherein modifying the first results based on the second resultscomprises utilizing a Kalman filter, a recursive filter, a particlefilter, or an apparatus to implement a prediction operation.
 7. Themethod as defined in claim 1, further comprising updating the pluralityof parameters based on the second results.
 8. The method as defined inclaim 1, further comprising predicting results based on the secondresults.
 9. The method as defined in claim 8, further comprisinggenerating a log based on the predicted results.
 10. The method asdefined in claim 1, further comprising generating a log associated withthe measurements obtained while drilling.
 11. The method as defined inclaim 1, further comprising generating a log associated with themeasurements obtained while drilling is temporarily suspended.
 12. Themethod as defined in claim 1, wherein at least one of the measurementsobtained while drilling or at least one of the measurements obtainedwhile drilling is temporarily suspended comprises measurementsassociated with a slowness time coherence map, velocity versusfrequency, formation compressional slowness, formation shear slowness,resistivity measurements, nuclear magnetic resonance measurements, ormeasurements associated with formation evaluation.
 13. The method asdefined in claim 1, wherein at least one of the first results or thesecond results comprises peaks with respect to slowness in a slownesstime coherence map.
 14. The method as defined in claim 1, wherein atleast one of the first results or the second results comprises a log ofslowness peaks versus depth.
 15. A method of predicting processingresults during a drilling operation, comprising: identifying a pluralityof parameters; processing measurements having a first amount of noiseand the plurality of parameters to generate first results; processingmeasurements having a second amount of noise and the plurality ofparameters to generate second results, wherein the first amount of noiseis greater than the second amount of noise; and predicting third resultsbased on the second results.
 16. The method as defined in claim 15,further comprising generating one or more logs that are associated withat least one of the first results, the second results, or the thirdresults.
 17. The method as defined in claim 15, wherein predicting thethird results based on the second results comprises utilizing a Kalmanfilter, a recursive filter, a particle filter, or an apparatus toimplement a prediction operation.
 18. The method as defined in claim 15,further comprising modifying the first results based on the secondresults.
 19. The method as defined in claim 18, wherein modifying thefirst results based on the second results comprises constraining thefirst results.
 20. The method as defined in claim 18, wherein modifyingthe first results based on the second results comprises identifying oneor more peaks within the first results that are not substantiallyassociated with noise.
 21. The method as defined in claim 20, whereinthe one or more peaks comprises one or more peaks with respect toslowness in a slowness time coherence map.
 22. The method as defined inclaim 15, further comprising updating the plurality of parameters basedon the second results.
 23. A drillstring, comprising: a measurementdevice to measure one or more parameters; a processor to process the oneor more measured parameters and one or more processing parameters togenerate results; and an apparatus to link results generated during afirst time interval and results generated during a second time interval.24. The drillstring as defined in claim 23, wherein the apparatus is topredict results based on at least some of the generated results.
 25. Thedrillstring as defined in claim 23, wherein the apparatus is to updatethe one or more processing parameters based on at least some of thegenerated results.
 26. The drillstring as defined in claim 23, whereinthe apparatus is to constrain at least some of the generated results.27. The drillstring as defined in claim 23, wherein the apparatuscomprises a Kalman filter or an apparatus to implement a predictionoperation.
 28. A method of selectively associating processing resultsduring a drilling operation, comprising: identifying a plurality ofparameters; processing measurements obtained while drilling and theplurality of parameters to generate first results; processingmeasurements obtained while drilling is temporarily suspended and theplurality of parameters to generate second results; comparing the firstand second results; and selectively associating the second results withat least a portion of the first results to optimize the first results.29. The method as defined in claim 28, wherein selectively associatingthe second results with at least the portion of the first resultscomprises linking one or more peaks within the second results with oneor more peaks within the first results.
 30. The method as defined inclaim 29, wherein the one or more peaks within the first results are notsubstantially associated with noise.